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Record W3198696835 · doi:10.1093/ibd/izab183

Insight into Inflammatory Bowel Disease Pathogenesis: Is the Answer Blowing in the Wind?

2021· article· en· W3198696835 on OpenAlexaff
Sari M. Herman, Karver Zaborniak, Çharles N. Bernstein

Bibliographic record

VenueInflammatory Bowel Diseases · 2021
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsUniversity of ManitobaUniversity of Toronto
Fundersnot available
KeywordsUlcerative colitisInflammatory bowel diseasePathogenesisImmunologyMedicineGenetic predispositionDiseaseInflammatory Bowel DiseasesCrohn's diseaseImmune systemImmune dysregulationPathology

Abstract

fetched live from OpenAlex

Inflammatory bowel diseases (IBD) including Crohn's disease and ulcerative colitis are conditions characterized by immune dysregulation to a trigger in those with a genetic predisposition. Environmental factors are thought to contribute to IBD, but no definite trigger has been identified. Aeroallergens have not been thoroughly investigated in their potential contribution to the pathogenesis to IBD. The geographic distribution of aeroallergens and IBD, the association of atopic disease with IBD, seasonality and IBD, and cross-reactive food allergens require further study with implications for targeted dietary and immunomodulatory therapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.245
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2021
Admission routes1
Has abstractyes

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